enquiry_fieldsEvery field of the Fax Line Index enquiry: key, label, type, whether required, help text and the allowed options where there are any. Pass answers to submit_enquiry keyed by field key.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden of explaining behavior. It does describe the output content well and implies this is a read-only introspection tool, but it does not explicitly state side-effect-free behavior, authentication needs, or response shape. For a simple field-list tool this is adequate but not richly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. The first sentence front-loads what the tool returns, and the second sentence provides an actionable connection to a sibling tool. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description must explain return values, and it does: it lists the fields and qualifiers (required, options, help text). It also gives a usage hook with submit_enquiry. Nothing essential for an agent to invoke and use this tool correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is nothing for the description to explain about inputs. The baseline for 0 parameters is 4, and the description adds useful context by noting that returned field keys are used as keys for submit_enquiry, which clarifies the meaning of one of the returned fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as returning all fields of the Fax Line Index enquiry and enumerates exactly what information is provided for each field: key, label, type, required status, help text, and allowed options. It also distinguishes itself from submit_enquiry by explaining that answers should be passed there keyed by field key. This makes the tool's purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys that this tool should be used to retrieve the enquiry structure before submitting answers, and explicitly directs the agent to submit_enquiry afterward. It does not explicitly mention when to use it over enquiry_describe or dataset_* siblings, but the context makes the intended workflow clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: schema, provenance, search, exact match, stats, top, compare, describe, fields, and submit. No overlap or ambiguity between dataset exploration and enquiry submission tools.
All tools follow a consistent snake_case pattern with clear prefixes (dataset_ and enquiry_) and descriptive suffixes (columns, search, stats, submit). Naming is uniform and predictable.
10 tools is well-scoped for a server that handles dataset exploration (7 tools) and an enquiry workflow (3 tools). Each tool earns its place and covers necessary operations without redundancy.
The dataset tools cover schema, provenance, search, exact match, statistics, top values, and comparison, while the enquiry tools cover description, field schema, and submission with confirmation. No obvious gaps for the stated purpose.